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From "Jiaqi Guo (Jira)" <>
Subject [jira] [Created] (SPARK-29333) Sample weight in RandomForestRegressor
Date Wed, 02 Oct 2019 16:49:00 GMT
Jiaqi Guo created SPARK-29333:

             Summary: Sample weight in RandomForestRegressor
                 Key: SPARK-29333
             Project: Spark
          Issue Type: New Feature
          Components: ML
    Affects Versions: 2.4.4
            Reporter: Jiaqi Guo

I think there have been some tickets that are related to this feature request. Even though
the tickets earlier have been designated with resolved status, it still seems impossible to
add sample weight to random forest classifier/regressor.

The possibility of having sample weight is definitely useful for many use cases, for example
class imbalance and weighted bias correction for the samples. I think the sample weight should
be considered in the splitting criterion. 

Please correct me if I am missing the new feature. Otherwise, it would be great to have an
update on whether we have a path forward supporting this in the near future.

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